Amazon technologies, inc. (20240331163). SYSTEMS FOR DETERMINING IMAGE MASKS USING MULTIPLE INPUT IMAGES simplified abstract
Contents
SYSTEMS FOR DETERMINING IMAGE MASKS USING MULTIPLE INPUT IMAGES
Organization Name
Inventor(s)
QIANLI Feng of SEATTLE WA (US)
RAGHU DEEP Gadde of BOTHELL WA (US)
ALEIX MARGARIT Martinez of SEATTLE WA (US)
SYSTEMS FOR DETERMINING IMAGE MASKS USING MULTIPLE INPUT IMAGES - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240331163 titled 'SYSTEMS FOR DETERMINING IMAGE MASKS USING MULTIPLE INPUT IMAGES
The abstract describes a method using a generative adversarial network (GAN) to identify sets of pixels in an image that correspond to different objects or a background. The GAN generates alternate images that retain the structural characteristics of the original image while modifying style characteristics, such as colors of pixels. These generated images can be analyzed to determine sets of pixels that change color in a similar manner across the images, which can be used as masks representing objects or background for image modification.
- The method utilizes a generative adversarial network (GAN) to identify sets of pixels in an image that correspond to different objects or a background.
- The GAN generates alternate images that retain the structural characteristics of the original image while modifying style characteristics, such as colors of pixels.
- Analyzing the generated images using a k-means clustering algorithm helps determine sets of pixels that change color in a similar manner across the images.
- Sets of pixels that change in a similar manner across the images can be used as masks representing objects or background for image modification without interfering with other objects.
Potential Applications: - Image segmentation for object recognition - Image editing tools for precise object isolation - Automated background removal in photography software
Problems Solved: - Accurate identification of objects in images - Efficient image editing without affecting other elements - Simplifying the process of image segmentation and masking
Benefits: - Enhanced image editing capabilities - Time-saving in object isolation tasks - Improved accuracy in image segmentation
Commercial Applications: Title: Advanced Image Editing Technology for Object Segmentation This technology can be used in photography software, graphic design tools, and image processing applications to streamline object isolation and background removal processes, catering to professionals in the creative industry.
Questions about the technology: 1. How does the use of a generative adversarial network (GAN) improve the process of identifying objects in images? 2. What are the potential limitations of using this method for image segmentation and object isolation?
Original Abstract Submitted
to identify sets of pixels in a first image that correspond to different objects or a background, a first image is provided to a generative adversarial network (gan). the gan determines alternate images that retain the structural characteristics of the first image, such as the locations and shapes of objects, while modifying style characteristics, such as the colors of pixels. the images generated by the gan may then be analyzed, such as by using a k-means clustering algorithm, to determine sets of pixels at the same location that change color in a similar manner across the set of images. a set of pixels that changes in a similar manner across the images generated by the gan may be used as a mask representing an object or background to enable modification of the image without interfering with other objects.
